Cluster names

HB13hpf

Named clusters after clustering at resolution 8, needed to resolve all rhombomeres into separate clusters.

DimPlot(HB13, reduction = "wnn.umap") + scale_color_igv()

Combining multiple clusters of same cell type.

Idents(HB13) <- "Clusters"
HB13 <- RenameIdents(HB13,
                       "CHB.1" = "CHB",
                       "CHB.2" = "CHB",
                       "CHB.3" = "CHB",
                       "SC.1" = "SC",
                       "SC.2" = "SC",
                       "SC.3" = "SC",
                       "r5.1" = "r5",
                       "r5.2" = "r5",
                       "MB.1" = "MB",
                       "MB.2" = "MB",
                       "MB.3" = "MB",
                       "MHB.1" = "MHB",
                       "MHB.2" = "MHB",
                       "MHB.3" = "MHB",
                       "MHB.4" = "MHB",
                       "MHB.5" = "MHB",
                       "FB.1" = "FB",
                       "FB.2" = "FB",
                       "FB.3" = "FB",
                       "FB.4" = "FB")

## Warning: Cannot find identity r5.2

## Warning: Cannot find identity r5.1

levels(HB13) <- c("FB","MB","MHB","r1","r1 & r2","r2","r3","r4","r5","r6",
                    "low_expression","unknown","Neuron","Ciliated","CHB","SC")
umap.HB13 <- DimPlot(HB13, reduction = "wnn.umap") + scale_color_igv()
umap.HB13

HB16hpf

Named clusters after clustering at resolution 6, needed to resolve all rhombomeres into separate clusters.

DimPlot(HB16, reduction = "wnn.umap") + scale_color_igv()

Combining multiple clusters of same cell type.

Idents(HB16) <- "Clusters"
HB16 <- RenameIdents(HB16,
                       "CHB.1" = "CHB",
                       "CHB.2" = "CHB",
                       "CHB.3" = "CHB",
                       "CHB.4" = "CHB",
                       "SC.1" = "SC",
                       "SC.2" = "SC",
                       "SC.3" = "SC",
                       "r5.1" = "r5",
                       "r5.2" = "r5",
                       "MB.1" = "MB",
                       "MB.2" = "MB",
                       "MHB.1" = "MHB",
                       "MHB.2" = "MHB",
                       "MHB.3" = "MHB")
levels(HB16) <- c("FB","MB","MHB","r1","r2","r3","r4","r5","r6",
                    "DorsNT & NC","Neuron","Ciliated","CHB","SC")
umap.HB16 <- DimPlot(HB16, reduction = "wnn.umap") + scale_color_igv()
umap.HB16

# Gene expression and chromvar activity plots

GetChromVarPlots <- function(object, motifs, reduction){
  DefaultAssay(object) <- "chromvar"
  mylist <- list()
  for(motif in 1:length(motifs)){
    p <- FeaturePlot(
      object = object,
      reduction = reduction,
      features = motifs[[motif]],
      min.cutoff = 'q10',
      max.cutoff = 2,
      pt.size = 1)  +
      ggtitle(paste(motifs[[motif]],names(motifs[motif]), sep = " ")) +
      theme(plot.title = element_text(size = 15)) + NoLegend()
    mylist[[motifs[[motif]]]] <- p
  }
  
  return(mylist)
}

GetChromVarPlotsPlusLegend <- function(object, motifs, reduction){
  DefaultAssay(object) <- "chromvar"
  mylist <- list()
  for(motif in 1:length(motifs)){
    p <- FeaturePlot(
      object = object,
      reduction = reduction,
      features = motifs[[motif]],
      min.cutoff = 'q10',
      max.cutoff = 2,
      pt.size = 1)  +
      ggtitle(paste(motifs[[motif]],names(motifs[motif]), sep = " ")) +
      theme(plot.title = element_text(size = 15))
    mylist[[motifs[[motif]]]] <- p
  }
  
  return(mylist)
}

# HB13 <- RunChromVAR(
#   object = HB13,
#   genome = BSgenome.Drerio.UCSC.danRer11,
#   assay = "peaks"
# )
# saveRDS(HB13, file = "../data/HB13hpf_neural.RDS")

# HB16 <- RunChromVAR(
#   object = HB16,
#   genome = BSgenome.Drerio.UCSC.danRer11,
#   assay = "peaks"
# )
# saveRDS(HB16, file = "../data/HB16hpf_neural.RDS")

HB13hpf

motif1.names <- c("CDX4","HOXB9","RARA::RXRG","HNF1B","EGR2","Mafb")
motifs1 <- c("MA1473.1","MA1503.1","MA1149.1","MA0153.2","MA0472.2","MA0117.2")
names(motifs1) <- motif1.names

HB13.cdx4 <- FeaturePlot(HB13, features = "cdx4", reduction = "wnn.umap", max.cutoff = 1.3)
HB13.hoxb7a <- FeaturePlot(HB13, features = "hoxb7a", reduction = "wnn.umap", max.cutoff = 1.3)
HB13.hoxb9a <- FeaturePlot(HB13, features = "hoxb9a", reduction = "wnn.umap", max.cutoff = 1.3)

HB13.exp <- HB13.cdx4 + HB13.hoxb7a + HB13.hoxb9a + plot_layout(ncol = 3, guides = "collect")
HB13.exp

HB13.cv.motif.legend <- GetChromVarPlotsPlusLegend(HB13, motifs1, "wnn.umap")
HB13.cv.list <- GetChromVarPlots(HB13, motifs1, "wnn.umap")
wrap_plots(HB13.cv.motif.legend)

HB13.motif1 <- HB13.cv.motif.legend[[1]] + HB13.cv.list[[2]] + plot_layout(ncol = 2, guides = "collect")
HB13.motif1

HB13.motif2 <- HB13.cv.motif.legend[[3]] + HB13.cv.list[[4]] + HB13.cv.list[[5]] + HB13.cv.list[[6]] + 
  plot_layout(ncol = 4, guides = "collect")
HB13.motif2

HB13.crabp2a <- FeaturePlot(HB13, features = "crabp2a", reduction = "wnn.umap", max.cutoff = 1.3)
HB13.rorcb <- FeaturePlot(HB13, features = "rorcb", reduction = "wnn.umap", max.cutoff = 1.3)
HB13.egr2b <- FeaturePlot(HB13, features = "egr2b", reduction = "wnn.umap", max.cutoff = 1.3)
HB13.mafba <- FeaturePlot(HB13, features = "mafba", reduction = "wnn.umap", max.cutoff = 1.3)

HB13.exp2 <- HB13.crabp2a + HB13.rorcb + HB13.egr2b + HB13.mafba + plot_layout(ncol = 4, guides = "collect")
HB13.exp2

HB16hpf

HB16.cv.motif.legend <- GetChromVarPlotsPlusLegend(HB16, motifs1, "wnn.umap")
HB16.cv.list <- GetChromVarPlots(HB16, motifs1, "wnn.umap")
wrap_plots(HB16.cv.motif.legend)

HB16.motif <- HB16.cv.motif.legend[[1]] + HB16.cv.list[[2]]  + 
  plot_layout(ncol = 2, guides = "collect")
HB16.motif

HB16.crabp2a <- FeaturePlot(HB16, features = "cdx4", reduction = "wnn.umap", max.cutoff = 1.3)
HB16.rorcb <- FeaturePlot(HB16, features = "hoxb9a", reduction = "wnn.umap", max.cutoff = 1.3)
HB16.egr2b <- FeaturePlot(HB16, features = "crabp2a", reduction = "wnn.umap", max.cutoff = 1.3)
HB16.mafba <- FeaturePlot(HB16, features = "rorcb", reduction = "wnn.umap", max.cutoff = 1.3)

HB16.exp <- HB16.crabp2a + HB16.rorcb + plot_layout(ncol = 2, guides = "collect")
HB16.exp

HB16.exp2 <- HB16.egr2b + HB16.mafba + plot_layout(ncol = 2, guides = "collect")
HB16.exp2

# Figure 1 combined plots

layout <- "
AABBB
AACCC
DDDDD
EEEEE
FFGGG
HHIII"

combined1 <- umap.HB13 + HB13.exp + HB13.motif1 + HB13.exp2 + HB13.motif2 + 
  umap.HB16 + HB16.exp + HB16.motif + HB16.exp2 + 
  plot_layout(design = layout)
combined1

layout <- "
AAAAAABBBB
CCCCCCDDDD
EEEEEEEEEE
FFFFFFFFFF
GGGGGGHHHH
IIIIIIHHHH"

combined2 <- umap.HB13 + umap.HB16 + 
  HB13.exp + HB13.motif1 + 
  HB13.exp2 + 
  HB13.motif2 + 
  HB16.exp + (HB16.motif + plot_layout(ncol = 1, guides = "collect")) + 
  HB16.exp2 + 
  plot_layout(design = layout, heights = c(2,1,1,1,1,1)) +
  theme(title = element_text(size = 3))
combined2

ggsave(filename = "Plots/Figure1.png", width = 15, height = 20, plot = combined2)

sessionInfo()

## R version 4.2.3 (2023-03-15)
## Platform: aarch64-apple-darwin20 (64-bit)
## Running under: macOS Monterey 12.6.2
## 
## Matrix products: default
## BLAS:   /Library/Frameworks/R.framework/Versions/4.2-arm64/Resources/lib/libRblas.0.dylib
## LAPACK: /Library/Frameworks/R.framework/Versions/4.2-arm64/Resources/lib/libRlapack.dylib
## 
## locale:
## [1] en_US.UTF-8/en_US.UTF-8/en_US.UTF-8/C/en_US.UTF-8/en_US.UTF-8
## 
## attached base packages:
## [1] stats4    stats     graphics  grDevices utils     datasets  methods  
## [8] base     
## 
## other attached packages:
##  [1] patchwork_1.1.2                     ggsci_3.0.0                        
##  [3] EnhancedVolcano_1.16.0              ggrepel_0.9.3                      
##  [5] ggplot2_3.4.2                       BSgenome.Drerio.UCSC.danRer11_1.4.2
##  [7] BSgenome_1.66.3                     rtracklayer_1.58.0                 
##  [9] Biostrings_2.66.0                   XVector_0.38.0                     
## [11] GenomicRanges_1.50.2                GenomeInfoDb_1.34.9                
## [13] IRanges_2.32.0                      S4Vectors_0.36.2                   
## [15] BiocGenerics_0.44.0                 Signac_1.10.0                      
## [17] SeuratObject_4.1.3                  Seurat_4.3.0.1                     
## 
## loaded via a namespace (and not attached):
##   [1] fastmatch_1.1-3             systemfonts_1.0.4          
##   [3] plyr_1.8.8                  igraph_1.4.2               
##   [5] lazyeval_0.2.2              sp_1.6-0                   
##   [7] splines_4.2.3               BiocParallel_1.32.6        
##   [9] listenv_0.9.0               scattermore_1.0            
##  [11] digest_0.6.31               htmltools_0.5.5            
##  [13] fansi_1.0.4                 magrittr_2.0.3             
##  [15] tensor_1.5                  cluster_2.1.4              
##  [17] ROCR_1.0-11                 globals_0.16.2             
##  [19] matrixStats_0.63.0          spatstat.sparse_3.0-1      
##  [21] colorspace_2.1-0            textshaping_0.3.6          
##  [23] xfun_0.39                   dplyr_1.1.2                
##  [25] crayon_1.5.2                RCurl_1.98-1.12            
##  [27] jsonlite_1.8.4              progressr_0.13.0           
##  [29] spatstat.data_3.0-1         survival_3.5-5             
##  [31] zoo_1.8-12                  glue_1.6.2                 
##  [33] polyclip_1.10-4             gtable_0.3.3               
##  [35] zlibbioc_1.44.0             leiden_0.4.3               
##  [37] DelayedArray_0.24.0         future.apply_1.10.0        
##  [39] abind_1.4-5                 scales_1.2.1               
##  [41] spatstat.random_3.1-4       miniUI_0.1.1.1             
##  [43] Rcpp_1.0.10                 viridisLite_0.4.2          
##  [45] xtable_1.8-4                reticulate_1.28            
##  [47] htmlwidgets_1.6.2           httr_1.4.6                 
##  [49] RColorBrewer_1.1-3          ellipsis_0.3.2             
##  [51] ica_1.0-3                   farver_2.1.1               
##  [53] pkgconfig_2.0.3             XML_3.99-0.14              
##  [55] sass_0.4.6                  uwot_0.1.14                
##  [57] deldir_1.0-6                utf8_1.2.3                 
##  [59] labeling_0.4.2              tidyselect_1.2.0           
##  [61] rlang_1.1.1                 reshape2_1.4.4             
##  [63] later_1.3.1                 munsell_0.5.0              
##  [65] tools_4.2.3                 cachem_1.0.8               
##  [67] cli_3.6.1                   generics_0.1.3             
##  [69] ggridges_0.5.4              evaluate_0.21              
##  [71] stringr_1.5.0               fastmap_1.1.1              
##  [73] ragg_1.2.5                  yaml_2.3.7                 
##  [75] goftest_1.2-3               knitr_1.42                 
##  [77] fitdistrplus_1.1-11         purrr_1.0.1                
##  [79] RANN_2.6.1                  pbapply_1.7-0              
##  [81] future_1.32.0               nlme_3.1-162               
##  [83] mime_0.12                   RcppRoll_0.3.0             
##  [85] compiler_4.2.3              rstudioapi_0.14            
##  [87] plotly_4.10.1               png_0.1-8                  
##  [89] spatstat.utils_3.0-2        tibble_3.2.1               
##  [91] bslib_0.4.2                 stringi_1.7.12             
##  [93] highr_0.10                  lattice_0.21-8             
##  [95] Matrix_1.6-1.1              vctrs_0.6.2                
##  [97] pillar_1.9.0                lifecycle_1.0.3            
##  [99] spatstat.geom_3.1-0         lmtest_0.9-40              
## [101] jquerylib_0.1.4             RcppAnnoy_0.0.20           
## [103] data.table_1.14.8           cowplot_1.1.1              
## [105] bitops_1.0-7                irlba_2.3.5.1              
## [107] httpuv_1.6.9                R6_2.5.1                   
## [109] BiocIO_1.8.0                promises_1.2.0.1           
## [111] KernSmooth_2.23-21          gridExtra_2.3              
## [113] parallelly_1.35.0           codetools_0.2-19           
## [115] MASS_7.3-60                 SummarizedExperiment_1.28.0
## [117] rjson_0.2.21                withr_2.5.0                
## [119] GenomicAlignments_1.34.1    sctransform_0.3.5          
## [121] Rsamtools_2.14.0            GenomeInfoDbData_1.2.9     
## [123] parallel_4.2.3              grid_4.2.3                 
## [125] tidyr_1.3.0                 rmarkdown_2.21             
## [127] MatrixGenerics_1.10.0       Rtsne_0.16                 
## [129] spatstat.explore_3.1-0      Biobase_2.58.0             
## [131] shiny_1.7.4                 restfulr_0.0.15

R Figure 1

Read data

Cluster names

HB13hpf

HB16hpf

HB13hpf

HB16hpf